EP2471183A1 - Procédé de communication de données de signal dans un système gnss au moyen de codes de convolution ldpc et système associé - Google Patents

Procédé de communication de données de signal dans un système gnss au moyen de codes de convolution ldpc et système associé

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Publication number
EP2471183A1
EP2471183A1 EP10782053A EP10782053A EP2471183A1 EP 2471183 A1 EP2471183 A1 EP 2471183A1 EP 10782053 A EP10782053 A EP 10782053A EP 10782053 A EP10782053 A EP 10782053A EP 2471183 A1 EP2471183 A1 EP 2471183A1
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EP
European Patent Office
Prior art keywords
signal data
ldpc
interleaved
encoded
parity check
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP10782053A
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German (de)
English (en)
Inventor
Suresh Vithal Kibe
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Indian Space Research Organisation
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Indian Space Research Organisation
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Publication date
Application filed by Indian Space Research Organisation filed Critical Indian Space Research Organisation
Publication of EP2471183A1 publication Critical patent/EP2471183A1/fr
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/03—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
    • H03M13/23—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using convolutional codes, e.g. unit memory codes
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/03—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
    • H03M13/05—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
    • H03M13/11—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits using multiple parity bits
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/27—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes using interleaving techniques
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/27—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes using interleaving techniques
    • H03M13/2703—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes using interleaving techniques the interleaver involving at least two directions
    • H03M13/2707—Simple row-column interleaver, i.e. pure block interleaving

Definitions

  • the present invention relates to the field of data communication in satellite communication systems.
  • the present invention specifically relates to a method of communicating signal data in a global navigation satellite system (GNSS) using low density parity check (LDPC) convolution codes and a system thereof under low signal to noise ratio condition.
  • GNSS global navigation satellite system
  • LDPC low density parity check
  • Communication systems transmit information from one source to another across various communication channels.
  • satellite communication systems are implemented to provide a basic communication, i.e. space-to-earth communication and space-to-space communication through the communication channels.
  • the information to be transmitted is encoded at source end.
  • channel coding techniques are implemented to the information before transmitting it to the communication channels.
  • the channel coding techniques are used to protect the data from channel noise.
  • FEC Forward Error Correction
  • BCH Bose-Chaudhuri-Hocquenghem
  • Convolutional codes Convolutional codes
  • Turbo Codes and LDPC block codes.
  • the channel coding techniques are judged based on their ability to approach Shannon's capacity limit, which states that as long as the transmission rate is less than the channel capacity, error free communication can be achieved.
  • Shannon's capacity limit which states that as long as the transmission rate is less than the channel capacity, error free communication can be achieved.
  • BCH codes, Convolutional codes and Turbo Codes are used for channel coding in many applications.
  • LDPC Low Density Parity Check
  • LDPC convolution codes are introduced as convolution counterparts of LDPC block codes.
  • LDPCCC is capable of achieving similar capacity approaching performance as LDPC block codes with simple encoding and decoding.
  • LDPCCC is suitable for continuous as well as block transmission.
  • iterative decoding offering excellent Bit Error
  • LDPCCC Low-power Code Code
  • LDPC block codes Such LDPCCC technique provides very good BER performance with simpler hardware implementation for error free performance over a variety of communication channels.
  • GNSS Global Navigation Satellite System
  • An object of the present invention is to provide a method of communicating signal data in GNSS system using LDPC convolution codes, which is capable of achieving error free performance over a GNSS communication channel for effective navigation data communication.
  • Another object of the present invention is to provide a system for communicating signal data in GNSS system using LDPC convolution codes, which provides good BER performance over a wide range of Signal-to-Noise ratios with simple hardware implementation.
  • the present invention which achieves this objective, relates to a method of communicating signal data in GNSS system using low density parity check (LDPC) convolution codes, comprising: at transmitting end, formatting signal data into a set of subframes. Each subframe of the signal data can be encoded in accordance with a parity check matrix defining Tanner graph representation of LDPC convolution codes.
  • the encoded signal data can be interleaved and added with a Sync word field to transmit an interleaved block of encoded signal data through a communication channel.
  • the interleaved block of encoded signal data can be de-interleaved after it is received from the communication channel.
  • the Tanner Graph shows the connectivity in time invariant parity check matrix.
  • a message passing technique is used to decode the LDPCCC encoded message.
  • the encoded signal data can be decoded through the message passing technique to obtain the signal data primitively transmitted at the transmitting end.
  • Such method is capable of achieving error free performance over the GNSS communication channel for effective navigation data communication, and also provides good BER performance over a wide range of Signal-to-Noise ratios.
  • the encoded signal data is block interleaved by writing into a memory matrix either column by column or row by row.
  • FSM Finite State Machine
  • the implementation of LDPCCC enables continuous decoding using pipeline decoders.
  • the interleaved block of encoded signal data is de-interleaved by reading out column by column if the signal data is interleaved row by row and vice versa.
  • the encoded signal data is block interleaved with an interleaving depth in accordance with error correction capability of the LDPC convolution codes.
  • the code rate is calculated based on the number of symbol nodes and the number of constraint nodes, where the number of symbol nodes is less than the number of constraint nodes.
  • the number of symbol nodes is configured with a time index associated with the symbol codes.
  • the syndrome former memory comprises a highest power of delay operator in said parity check matrix and index of Galois field.
  • the signal data comprises navigation data structure. Each subframe of the signal data is configured with identity page bits, navigation data bits, cyclic redundancy check (CRC) bits and termination bits. The termination bits depend on an encoded codeword of each subframe excluding the termination bits of the signal data for driving a finite state machine.
  • the present invention which achieves this objective, relates to a system for communicating signal data in GNSS system using low density parity check (LDPC) convolution codes, comprising: at transmitting end, a data formatter in communication with a data source for formatting signal data into a set of subframes.
  • An encoder is in communication with the data formatter for constructing a parity check matrix to define Tanner graph representation of LDPC convolution codes to encode each subframe of the signal data.
  • An interleaver is associated with the encoder for carrying out block interleaving and addition of a sync word field on the encoded signal data.
  • a transmitter is associated with the interleaver for transmitting an interleaved block of encoded signal data through a communication channel.
  • a de- interleaver is in communication with a receiver for de-interleaving the interleaved block of encoded signal data received from the receiver through the communication channel.
  • a decoder in communication with said de-interleaver for decoding the encoded signal data through a message passing technique to obtain the signal data primitively transmitted at the transmitting end.
  • FIG. 1 illustrates a schematic block diagram of a system for communicating signal data in GNSS system using LDPC convolution codes, in accordance with an exemplary embodiment of the present invention
  • FIG. 2a illustrates a typical navigation data structure for a GNSS system, in accordance with an exemplary embodiment of the present invention
  • FIG. 2b illustrates a detailed view of a subframe of the navigation data structure of FIG. 1a, in accordance with an exemplary embodiment of the present invention
  • FIG. 2c illustrates forward error correction (FEC) on the subframes of the navigation data structure of FIG. 2a, in accordance with an exemplary embodiment of the present invention
  • FIG. 3 illustrates a typical example of BER performance in the navigation data structure for the GNSS system, in accordance with an exemplary embodiment of the present invention
  • FIG. 4 illustrates a flowchart of a method of communicating signal data in GNSS system using LDPC convolution codes, in accordance with an exemplary embodiment of the present invention.
  • GNSS Global Navigation Satellite Systems
  • L1 signal Global Navigation Satellite Systems
  • L2 signal 1215-1300 MHz
  • L5 signal 1164 - 1215 MHz
  • the signal and data structure for each of these GNSS systems are different.
  • the present invention describes implementation of LDPC Convolution Codes (LDPCCC) for signal and data structure in the GNSS systems, in particular medium earth orbit or geostationary orbit satellite navigation system.
  • FEC Forward Error Correction
  • the LDPCCC provides a systematic comparison of the codes for finite block lengths.
  • the LDPCCC is capable of achieving Shannon capacity approaching performance with iterative decoding.
  • the LDPCCC provides encoding simplicity through shift register based systematic real time encoding of the navigation data structure.
  • the LDPCCC implementation also provides the excellent bit error rate performance in the presence of Additive White Gaussian Noise (AWGN) and for a Binary Symmetrical Channel (BSC).
  • AWGN Additive White Gaussian Noise
  • BSC Binary Symmetrical Channel
  • the LDPCCC facilitates better performance than the LDPC block codes even under very low Energy per Bit to Noise Density ratios (Eb/No) conditions.
  • Eb/No Energy per Bit to Noise Density ratios
  • the communication system can be configured with a transmitting section, a receiving section and a communication channel 105.
  • the transmitting section is arranged with a navigation data formatter 101, a forward error correction (FEC) encoder 102, an interleaver 103 and a transmitter 104, whereas the receiving section is arranged with a receiver 106, a de-interleaver 107 and a FEC decoder 108.
  • FEC forward error correction
  • encoding and decoding of navigation data message 109 can be implemented by means of LDPC convolution codes.
  • the FEC encoder 102 and decoder 108 can be referred as LDPCCC encoder and decoder only for the purpose of explanation.
  • the communication channel 105 includes, but not limited to satellite, optical fibre, landline and copper cable.
  • the LDPCCC encoder 102 and decoder 108 are coupled together at the transmission section.
  • the transmitting and receiving sections are positioned at different places, then the LDPCCC encoder 102 and decoder 108 are placed at the transmitting and receiving sections, respectively.
  • Such LDPCCC encoder 102 and decoder 108 are necessary for data communication for low Eb/No.
  • FEC is required when the Eb/No is below 6.5 dB.
  • raw navigation signal data 109 can initially be formatted into a set of subframes using the navigation data formatter 101, as shown in FIG. 2a, which illustrates a typical navigation data structure for a GNSS system, in accordance with an exemplary embodiment of the present invention.
  • the navigation data formatter 101 is in communication with a data source having the navigation data 109.
  • the navigation data structure 109 for the GNSS system containing 1500 bits can be formatted into subframes 1 to 5, where each subframe contains 300 bits.
  • Each subframe 1 to 5 of the navigation data structure 109 is configured with a set of fields, like page, navigation data, cyclic redundancy check (CRC) and tailbits, as shown in FIG. 2b, which illustrates a detailed view of a subframe of the navigation data structure 109 of FIG. 1a, in accordance with an exemplary embodiment of the present invention.
  • Each subframe 1 to 5 (292 bits) can be identified by a page (6 bits) followed by navigation data (256 bits), CRC (24 bits) and tailbits (6 bits) as per forward error correction (FEC).
  • FEC forward error correction
  • the LDPCCC encoder 102 is in communication with the navigation data formatter 101 to encode the navigation data structure 109 by means of forward error correction (FEC).
  • FEC forward error correction
  • the FEC encoded subframe is interleaved and added with a Sync word field (16 bits).
  • the encoder 102 and decoder 108 can normally be a Viterbi maximum likelihood encoder and decoder.
  • the size of the memory is 6 and hence the tail bits are also 6.
  • This convolutional code improves Eb/No performance by about 5 dB with soft decision encoding and decoding.
  • the value of termination bits depends on the encoded codeword of the navigation data frame excluding termination bits.
  • the termination bits drive the FSM (finite state machine) into such a state that zero input message gives a zero codeword.
  • the number of termination bits increases with ms and is greater than or equal to ms. Also, the number of termination bits can be a multiple of j, i.e. 3 in this example, which can further be adjusted to optimize the code performance.
  • the LDPC convolutional codes are suitable for practical implementation in a number of different communication scenarios, including continuous transmission as well as block transmission in frames of arbitrary size. Also, each subframe explained in FIG2 contains a set of tail bits which drives the FSM to initial state, promising more efficient coding than convolutional codes or LDPC-block codes.
  • the VLSI implementation of the encoder 102 and decoder 108 is facilitated due to the LDPC convolutional structure of the Tanner graph.
  • the LDPC convolutional codes provide better BER performance than other codes as shown in the FIG 3 at a given Eb/No.
  • the LDPCCC encoding matrix (H) consists of only a few 1's in any row or column, where the remaining elements in the LDPCCC encoding matrix are zero.
  • the number of 1's in any column of the LDPCCC encoding matrix is denoted by j and the number of 1's in any row is denoted by k.
  • the Tanner graph of the LDPC convolution code is similar to the Tanner graph of the block code.
  • the symbol nodes corresponding to each row and constraint nodes corresponding to each column of the syndrome former H ⁇ are represented on a Tanner graph.
  • a line called an edge connects the symbol node to a constraint node if the entry in the corresponding row and column of H ⁇ is "1".
  • j is a number of symbol nodes, i.e. the number of rows of the parity check matrix
  • k is a number of constraint nodes, i.e. the number of columns of the parity, check matrix
  • m s is a syndrome former memory, i.e. the highest power of D in the parity check matrix.
  • rate of the code (R) can be formulated as,
  • the code symbols of the LDPC convolutional code contain a time index associated with the code symbols.
  • the LDPC convolutional codes are not limited to a fixed block length (N) as LDPC block codes, i.e. a single code can be utilized for several block lengths, where N is the length of data in the typical LDPC block code.
  • N is the length of data in the typical LDPC block code.
  • the complexity of encoding of the LDPC convolution code is low using shift registers.
  • the LDPC convolutional codes also achieve continuous decoding using pipeline decoders.
  • the LDPC convolutional codes provide better performance than the LDPC block codes.
  • the connectivity of nodes in the Tanner graph structure at different times is identical for a time invariant convolutional code, which leads to significant reduction in storage requirement for implementing these LDPCCC codes.
  • the time invariant LDPCCC codes can be algebraically constructed using quasi-cyclic LDPC codes.
  • a code is quasi cyclic if for any cyclic shift of a code word by p places the resulting word is also a code word.
  • the block Interleaving and addition of sync word is performed on the encoded navigation data using the interleaver 103 in order to make the channel robust towards burst errors.
  • the encoded navigation data can be interleaved before transmitting the navigation data to the communication channel 105. If the burst errors occur in the encoded navigation data, then the burst errors can effectively determined as distributed errors after de-interleaving of the navigation data. This type of burst errors can be corrected by the LDPCCC decoder 108.
  • the interleaver 103 and de-interleaver 107 are in communication with the LDPCCC encoder 102 and decoder 108, respectively.
  • the bits of the navigation data are written into an n*k memory matrix having n columns and k rows.
  • the navigation data is written either column by column or row by row to obtain the interleaved block and read in the reverse manner.
  • the transmitter 104 is associated with the interleaver 103 for transmitting the interleaved navigation data through the communication channel 105.
  • the receiver 106 is associated with the de-interleaver 107 for de-interleaving the interleaved block of encoded navigation data received from the communication channel 105.
  • the bits of interleaved block of the encoded navigation data are written into the memory matrix row by row and read out column by column to obtain the de-interleaved navigation data at the receiving section.
  • the block interleaving of 8x73 is possible for the encoded navigation data as shown in FIG. 2c.
  • the value of k can usually be referred as interleaving depth and selected according to the error correction capability of code. If the convolution code utilizes a constraint length of 7, single bit errors in each block equal can be corrected to the constraint length. In this scenario, the interleaving depth can be selected to be a minimum of 7.
  • the LDPCCC decoder 108 is in communication with the de- interleaver 107 for decoding the encoded navigation data after de-interleaving the received navigation data, in order to obtain the navigation. data 109 primitively transmitted at the transmitting section.
  • the LDPCCC decoder 108 can be implemented by calculating r for each constraint node using the formula given below, where,
  • r is the message sent from the symbol node to the constraint node.
  • ci is the Log Likelihood Ratio (LLR) of the given encoded bit that is fed to the symbol node.
  • y is all the neighboring nodes of / leaving/ Also, q for each symbol node can be calculated using the formula given below,
  • q is the message sent from the constraint node to the symbol node.
  • qji calculates cumulative probability of the message from the constraint node satisfying the parity check equation.
  • r,j calculates the total probability of the symbol node being the bit satisfying the parity check equation.
  • LLR log— , where p x is the
  • the nominal value of LLR can be considered as 16.
  • the BER performance of LDPCCC measured with BSC and AWGN after introducing AWGN noise in rate half LDPCCC is shown in FIG. 2a & 2b, where the number of iterations is generally taken as 10.
  • Such algorithm can be further modified to improve the BER performance in the navigation data structure 109 for the GNSS system.
  • the LDPCCC encoder 102 and decoder 108 can be implemented using VC++ software.
  • the LDPCCC code is an ingenious algorithm with complexity about 1/15 th of an equivalent algorithm using LDPC code.
  • the decoding delay for this LDPCCC algorithm is 3.7 seconds whereas the decoding delay of the LDPC code is more than 11.5 seconds.
  • the LDPCCC algorithm is easily modifiable by changing the initially defined variables.
  • the number of lines of C-code is 260, which is the lowest possible in implementing of the LDPCCC algorithm.
  • the number of tail-bits in this LDPCCC algorithm is 6.
  • the LDPCCC algorithm determines the value of the six termination bits, which depend on the encoded codeword of the frame excluding termination bits.
  • the finite and small number of tail bits helps in simple and speedier implementation of the LDPCCC encoder and decoder algorithm.
  • the termination bits drive the finite state machine (FSM) into such a state that zero input message provides a zero codeword.
  • FSM finite state machine
  • the LDPC convolution codes are simple to encode, since the original code construction yields to a shift register based systematic encoding.
  • the LDPC convolution codes are suitable for transmission of continuous data as well as block transmissions in frames of arbitrary size whereas the LDPC transmits block of fixed length only. For a given complexity, the LDPC convolution codes have better performance than the LDPC block codes.
  • the LDPCCC codes provide excellent BER performance under AWGN 1 and are extremely useful for large values of data bits N. Also, it can be used with good BER performance for shorter number of data symbols in GNSS navigation data.
  • the architecture of the LDPCCC codes is more amenable to pipelining because of feed forward architecture, which facilitates higher clock speeds and continuous decoding.
  • VLSI implementation of LDPCCC codes is based on replicating identical units called processors.
  • a complete decoder can be constructed by concatenating a number of processors together, where the convolutional structure of Tanner graph aids VLSI implementation.
  • the size of LDPCCC processor is an order of magnitude less than LDPC block code.
  • the routing complexity within a processor is also an order of magnitude less than the LDPC block code.
  • the LDPCCC facilitates very good BER performance with simpler hardware implementation, and is utilized for error free performance over a variety of communication channels, especially in the navigation data structures, which require good BER performance over a wide range of Signal-to-Noise ratios commonly represented by Energy per Bit to Noise Density ratios (Eb/No).
  • the LDPCCC technique is suitable for computer-to-computer communication, satellite communication links, large file transfers over terrestrial, cable, optical fibre links or global navigation satellite system (GNSS) links.
  • GNSS global navigation satellite system
  • navigation signal data 109 to be transmitted can be formatted into a set of subframes at transmitting end.
  • Each subframe of the signal data is configured with identity page bits, navigation data bits, cyclic redundancy check (CRC) bits and termination bits.
  • the termination bits depend on an encoded codeword of each subframe excluding the termination bits of the signal data for driving a finite state machine.
  • each subframe of the navigation signal data can be encoded in accordance with a parity check matrix defined by a Tanner graph representation of the LDPC convolution codes.
  • the parity check matrix can be defined by a number of symbol nodes, a number of constraint nodes, a code rate and a syndrome former memory.
  • the number of symbol nodes is a number of rows of the parity check matrix whereas the number of constraint nodes is a number of columns of the parity check matrix.
  • the number of symbol nodes can be configured with a time index associated with the symbol codes.
  • the syndrome former memory is a highest power of delay operator in the parity check matrix and index of Galois field.
  • the code rate can be calculated based on the number of symbol nodes and the number of constraint nodes, where the number of symbol nodes is less than the number of constraint nodes.
  • the interleaved block of encoded signal data can be de-interleaved by reading out column by column if the signal data is interleaved row by row and vice versa.
  • the encoded signal data can be block interleaved with an interleaving depth in accordance with error correction capability of the LDPC convolution codes.
  • the interleaved block of encoded signal data can be de-interleaved after receiving it from the communication channel.
  • the encoded signal data can be decoded based on a message passing technique to obtain the navigation signal data 109 primitively transmitted at the transmitting end.
  • Such method is capable of achieving error free performance over the GNSS communication channel for effective navigation data communication, and also provides good BER performance over a wide range of Eb/No ratios.
  • the LDPC convolutional codes are capable of achieving Shannon capacity approaching performance with iterative decoding. Moreover, the LDPCCC implementation also provides the excellent bit error rate performance in the presence of Additive White Gaussian Noise (AWGN) and for a Binary Symmetrical Channel (BSC). Thus, the LDPCCC facilitates better performance than the LDPC block codes.
  • LDPC convolutional codes are suitable for practical implementation in a number of different communication scenarios, including continuous transmission as well as block transmission in frames of arbitrary size. Also, each subframe explained in FIG2 contains a set of tail bits which drives the FSM to initial state, promising more efficient coding than convolutional codes or LDPC-block codes.
  • LDPC convolutional codes Computational complexity for LDPC convolutional codes is very less as compared to LDPC block codes for same iterations and same frame length.
  • Processor Complexity of LDPC convolutional codes is as compared to LDPC block codes per iteration.
  • Decoding delay for LDPC convolutional codes is negligible as compared to for LDPC block codes.
  • Memory requirement for LDPC convolutional codes is much less as compared to that for LDPC block codes. Termination bits are fixed in number and are equal to 6 in the configuration described. Thus, ending the long held problem of variable length termination of the frame.
  • routines of particular embodiments including C, C++, Java, assembly language, etc.
  • Different programming techniques can be employed such as procedural or object oriented.
  • the routines can execute on a single processing device or multiple processors.
  • steps, operations, or computations may be presented in a specific order, this order may be changed in different particular embodiments. In some particular embodiments, multiple steps shown as sequential in this specification can be performed at the same time.
  • Particular embodiments may be implemented in a computer-readable storage medium for use by or in connection with the instruction execution system, apparatus, system, or device.
  • Particular embodiments can be implemented in the form of control logic in software or hardware or a combination of both.
  • the control logic when executed by one or more processors, may be operable to perform that which is described in particular embodiments.
  • one or more of the elements depicted in the drawings/figures can also be implemented in a more separated or integrated manner, or even removed or rendered as inoperable in certain cases, as is useful in accordance with a particular application. It is also within the spirit and scope to implement a program or code that can be stored in a machine-readable medium to permit a computer to perform any of the methods described above.

Abstract

L'invention concerne un procédé et un système de communication de données de signal dans un système GNSS au moyen de codes de convolution LDPC. Ce procédé comprend le formatage des données de signal en un ensemble de sous-trames, au niveau de l'extrémité émettrice. Chaque sous-trame des données de signal peut être codée selon une matrice de contrôle de parité représentant les codes de convolution LDPC dans un graphique de Tanner. Les données de signal codées peuvent être entrelacées et additionnées d'un champ de marqueur pour transmettre un bloc entrelacé de données de signal codées via un canal de communication. Au niveau de l'extrémité réceptrice, le bloc entrelacé des données de signal codées peuvent être désentrelacées après réception par le canal de communication. Le graphique de Tanner représente la connectivité dans une matrice de contrôle de parité à temps invariable. Une technique de passage de messages est utilisée pour décoder le message codé par codes de convolution LDPC (LDPCCC). Pour obtenir les données de signal initialement transmises depuis l'extrémité émettrice, les données de signal codées peuvent être décodées par application de la technique de passage de messages. Ces procédé et système peuvent avoir un fonctionnement sans erreur sur le canal de communication GNSS, ce qui permet une communication de données de navigation efficace, ainsi qu'un fonctionnement BER satisfaisant dans une gamme étendue de rapports signal sur bruit.
EP10782053A 2009-08-27 2010-08-27 Procédé de communication de données de signal dans un système gnss au moyen de codes de convolution ldpc et système associé Ceased EP2471183A1 (fr)

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Publication number Priority date Publication date Assignee Title
WO2013097174A1 (fr) 2011-12-30 2013-07-04 华为技术有限公司 Procédé, dispositif et système de codage/décodage de correction d'erreurs sans circuit de retour
FR2993369B1 (fr) * 2012-07-11 2017-10-13 Centre Nat D'etudes Spatiales Signal radio gnss pour une synchronisation amelioree
WO2014179937A1 (fr) * 2013-05-07 2014-11-13 华为技术有限公司 Procédé, dispositif et système de codage et de décodage
WO2015137712A1 (fr) * 2014-03-14 2015-09-17 Samsung Electronics Co., Ltd. Procédé et appareil de régulation de profondeur d'entrelacement
CN105099599B (zh) * 2014-04-16 2019-12-27 上海澜至半导体有限公司 交织、解交织方法以及相应的装置
KR102265052B1 (ko) * 2014-12-17 2021-06-15 삼성전자주식회사 적응적으로 인터리빙 깊이를 결정하는 인터리빙 방법 및 장치
KR102287616B1 (ko) * 2015-02-16 2021-08-10 한국전자통신연구원 길이가 64800이며, 부호율이 2/15인 ldpc 부호어 및 256-심볼 맵핑을 위한 비트 인터리버 및 이를 이용한 비트 인터리빙 방법
CN106767383A (zh) * 2016-11-11 2017-05-31 清华大学 基于连续运行gnss站信噪比数据的积雪深度的测量方法
MX2019005932A (es) 2016-11-23 2019-11-12 Fraunhofer Ges Forschung Receptor, transmisor, red de comunicacion, se?al de datos y metodo para mejorar un proceso de retrasmision en una red de comunicacion.
JP7124276B2 (ja) * 2017-08-14 2022-08-24 富士通株式会社 伝送装置、及び誤り訂正方法
EP3544248A1 (fr) * 2018-03-20 2019-09-25 Centre National D'etudes Spatiales Fonction de détection adaptive basée sur une estimation statistique de canal de propagation pour des récepteurs gnss
CN112165338B (zh) * 2020-09-30 2023-05-02 电子科技大学 一种卷积码随机交织序列交织关系的估计方法
CN112865853B (zh) * 2020-12-30 2023-01-10 广东省电信规划设计院有限公司 卫星的数据传输参数优化方法、装置及通信系统
CN113132058B (zh) * 2021-02-23 2023-05-05 龙文华丰(北京)科技有限公司 一种基于高斯约当消元的改进卷积交织盲识别方法
CN113891065B (zh) * 2021-09-09 2023-11-28 武汉中海庭数据技术有限公司 一种单帧图像传输延时测量方法和系统

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100122143A1 (en) * 2007-03-27 2010-05-13 Hughes Network Systems, Llc Method and system for providing low density parity check (ldpc) coding for scrambled coded multiple access (scma)
US8619974B2 (en) * 2007-03-27 2013-12-31 Hughes Network Systems, Llc Method and system for providing spread scrambled coded multiple access (SSCMA)
US20110047434A1 (en) * 2008-04-28 2011-02-24 Qualcomm Incorporated Wireless communication of turbo coded atsc m/h data with time diversity

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
ZHENGANG CHEN ET AL: "Low-density parity-check convolutional codes applied to packet based communication systems", PROC., IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, GLOBECOM '05, ST. LOIUS, MO, USA, vol. 3, 28 November 2005 (2005-11-28) - 2 December 2005 (2005-12-02), pages 1250 - 1254, XP010880931, ISBN: 978-0-7803-9414-8, DOI: 10.1109/GLOCOM.2005.1577852 *

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